The widespread use of prostate-specific antigen (PSA) testing has enabled physicians to closely monitor patients who have been treated for prostate cancer. This has resulted in the detection of rising PSA levels among prostate cancer survivors without clinical evidence of disease. Patients who experience a rising PSA or biochemical failure (circa 60,000 patients/year) have to deal not only with the possibility of a cancer recurrence, but also with treatment decisions, specifically, if and when treatment should be started and what kind of treatment to choose. All treatments (except for observation) have significant side-effects and will influence quality of life. Decision making in such circumstances is difficult at best. Using a cognitive-affective self-regulation framework we are focusing on the influence of affect and cognition on decision making for a rising PSA level. Specifically, the primary goal of this application is to explore the existence and influence of three affect functions in decision making: a) affect as information;b) affect as a spotlight used to highlight specific information;and c) affect as a motivator for action. A second objective is to integrate findings on affect functions into the larger theoretical self-regulation framework. We will use a mixed-methods approach consisting of quantitative data assessments and qualitative in-depth interviews to collect data on N = 168 patients diagnosed with biochemical failure. The goal of the quantitative data assessment is to discover the structure of the decision making process, while the qualitative approach is directed toward discovering meaning the patient assigns to the disease and its treatment options. Questionnaire data will be assessed at baseline and 4 times over a 12 months period. In-depth, in-person interviews will be conducted among those patients who have made a decision to opt for active treatment and among those patients who at the end of the study period opt to continue with watchful waiting (i.e., maintain the status quo). Post treatment, decision patients are followed, on an exploratory basis, to assess decisional conflict and quality of life. We hypothesize that cancer specific negative affect will influence risk perceptions;that a positive affective response to treatment or observation will lead to differential evaluation of pros and cons of a treatment option;and that negative affect will predict treatment over observation. We will use regression analyses to evaluate the predictive power of affect functions and qualitative data approaches to illustrate the role of affect in decision making. On a practical level, findings from this research will contribute to our understanding of how patients actually make decisions (a descriptive model). In addition, we will explore how this differs from an ideal decision making process (a normative model), and how this process might be improved (a prescriptive model). On a theoretical level, the integration of findings will advance self-regulation theory and inform decision making and health behavior choice in general.